As artificial intelligence matures and expands within enterprises, leaders across industries are struggling to get everyone on board. At the same time, they must manage customer and employee relationships amid shifting expectations in an era of digital transformation.
The latest ideas from MIT Sloan Management Review consider how to overcome the barriers of AI implementation and commit to putting AI tools into production. Leaders also learn how to know what customers want, how to avoid a toxic workplace, and how to conduct effective brainstorming sessions.
Overcome 3 common barriers to using AI tools
AI-based decision-making tools have the potential to increase efficiency, improve service quality, reduce costs and increase revenue. But this only happens if employees use the tools. Often they don’t.
AI projects encounter resistance from frontline workers in industries ranging from healthcare to retail, MIT Sloan professorwrites, along with co-authors Mark Sendak and Suresh Balu. This resistance usually stems from three conflicts of interest between AI developers, business leaders, and end users. A more holistic approach to implementation can break through these barriers.
Problem 1: AI tools benefit the organization, not the end user. This is common when organizations use predictive analytics to drive downstream value, as it forces end users to enter data or make decisions unrelated to their role. To address this, AI developers need to focus on issues end users face in their day-to-day work, while managers need to provide tangible incentives for using the tools.
Problem 2: Tools require extra labor from the end user. A greater involvement in AI tools, especially those outside of typical employee technology workflows, only makes the job more difficult. Tools that can automate data retrieval, testing, and validation, and provide visibility into the applications employees are already using, should minimize the impact on end-user workloads.
Problem 3: Tools limit the end user’s autonomy. Prescriptive tools that provide evidence-based decision support — and track or anyone accepting recommendations — violate the intuitive judgment of end users. AI tools should help end users make decisions, while leaving the “last call” to them. To understand this give and take, the end user must be involved early in the development cycle.
Know the 5 traits of an ‘AI powerhouse’ company
Nearly two-thirds of companies have yet to see value from their AI investments, and 45% view AI as a risk to their business in some way. That’s because these companies tend to play with AI and have not yet put their AI tools into production, write Thomas H. Davenport, a visiting scientist at the MIT Initiative on the Digital Economy, and Randy Bean, CEO of NewVantage Partners. .
Mastercard is not one of those companies. Support for AI starts with CEO Michael Miebach and is built through a combination of acquisition and in-house talent development. The example of Mastercard, a self-described “AI powerhouse”, suggests that there are: five pillars of a company that is all-in on AI†
- Powering products and services. Mastercard started with fraud detection, but plans to apply AI to all parts of the payment cycle.
- Managing internal operations. Predictive applications support processes ranging from business forecasting (with 99% accuracy) to server maintenance.
- Supporting customers. Mastercard is working with enterprise customers to identify their own use cases for AI — and create a proof of concept in just six weeks.
- Pursuing AI for good. The company runs AI projects focused on community development, microfinance and building data science talent in underserved areas.
- Prioritize ethical AI. In its AI development efforts, Mastercard emphasizes customer ownership, control and ability to benefit from their own data.
Rethink these assumptions about what customers want
Assumptions can guide business leaders to useful decisions and align stakeholders with common views, MIT Sloan lead researcher explained in a recent webinar. However, assumptions also reinforce unconscious biases and shield innovations that go against the grain. In an ever-changing world, companies need to rethink these 5 common assumptions about customer expectations†
Customers appreciate the human touch. Many customers prefer self-service and think that a human slows down the interaction.
Personal experiences are better than digital. The digital experience enables businesses to reach a global audience while providing greater convenience at a lower cost.
People don’t pay full price for digital. People pay for value, and convenience is an important part of that value. By providing convenience, digital can provide significant value.
Service restrictions from the Pandemic era are only temporary. It turns out that certain services cut during the pandemic, such as daily turndowns in hotel rooms, may be overvalued.
The old way was the right way. Traditional business models don’t just predate the pandemic; they can be older than the smartphone, the internet or even the telephone.
When business leaders question these assumptions, these are the questions to keep in mind:
- Who is the human salesperson helping: the customer or our inefficient and outdated internal processes?
- How do we optimize personal and digital interactions for customers, not just ourselves?
- How do preferences differ per customer segment?
- When is digital better – and can we ask for more instead of less?
- How many do customers have? For real do we need the services we are cutting back on during the pandemic?
Avoid the 5 Signs of a Toxic Corporate Culture
Many characteristics of a company can contribute to a bad culture, but there is a difference between culture elements that are annoying or disappointing and those that are really toxic. In a survey of more than 1.3 million Glassdoor reviews, MIT Sloan senior lecturer and co-authors identified Five Common Characteristics of a Toxic Corporate Culture† These are the characteristics that have the greatest negative impact on how employees value the company culture.
- Not included employee representation based on gender, race, sexual identity and orientation, disability and age – coupled with a culture of favoritism and general unwritten favoritism.
- disrespectful treatment of employees as evidenced by a lack of consideration, courtesy and dignity for others.
- unethical and dishonest conduct – or worse, failure to comply with applicable state and federal regulations.
- Killer work environments in which colleagues actively undermine each other.
- offensive management that openly bullies, condescends, or puts down employees.
A toxic corporate culture comes at a high cost. Companies are finding it more difficult to attract and retain talent, while retaining employees are less productive and more likely to develop chronic illness. And no one is immune: Even companies with high corporate culture ratings are likely to have “pockets of cultural toxicity” with business units, functions, or geographies.
Bring constructive criticism to the creative process
The primary basic rule for brainstorming sessions — no criticism — dates back to the late 1940s. But recent research suggests: constructive criticism can encourage extra creativity and imagination† The key, according to MIT Sloan associate professor is understanding the context of the brainstorming exercise.
In a cooperative context where group members’ goals are aligned, criticism can stimulate creativity. In a more competitive session—one in which participants are encouraged to prioritize ideas, for example, or one where groups fall squarely into two camps, such as employees and managers—criticism is more likely to lead to conflict.
Before having a brainstorming session, leaders need to understand the dynamics of the teams coming together. If conflict is likely, organizations can opt for one free-flowing ideas session combined with critique, followed by a session to review ideas. In such a setup, team members are less likely to edit their ideas – and the creative process is less likely to be undermined.